支持向量机优化的线性插值法在变压器油温预处理中的应用
摘要：变压器油温的预处理方法直接影响到油温的预测精度，进而影响变压器内部热状态的评估。基于支持向量机(support vector machine，SVM)和线性插值原理提出一种SVM优化的线性插值法，提高变压器油温预处理的准确性。首先利用SVM对变压器油温数据进行总体判别，确定数据异常点的大致范围；然后建立基于加权优化的线性插值法计算模型并设定判别变压器油温数据异常点的阈值；之后，给出变压器油温数据异常点位置及数量精确判别式； 最后基于相关性加权原理和钟形函数，对变压器油温数据进行了平滑处理。算例结果验证了该方法的有效性与可行性。
Abstract:The preprocessing method of transformer oil temperature directly affects the prediction accuracy of transformer oil temperature as well as the assessment on the inner thermal state within the transformer. Based on support vector machine (SVM) optimization and the principle of linear interpolation, a method to improve the preprocessing accuracy of transformer oil temperature was proposed. Firstly, the SVM was utilized to overall distinguish the data of transformer oil temperature to determine the approximate range of the point with data exception. Secondly, a calculation model based on weighted optimized linear interpolation was established and the threshold, by which the point with abnormal data of transformer oil temperature could be determined, was set. Thirdly, an accurate discriminant to determine both positions of points with abnormal data of transformer oil temperature and the amount was given. Finally, on the basis of the principle of correlation weighting and the bell shaped function, the smoothing processing of transformer oil temperature was performed. The effectiveness and feasibility of the proposed method are verified by simulation results.
标题：支持向量机优化的线性插值法在变压器油温预处理中的应用
英文标题：Application of Prediction Accuracy Interpolation Method Based on Support Vector Machine Optimization in Transformer Oil Temperature Preprocessing
作者：谭风雷, 张兆君, 吴兴泉, 武广斌, 马宏忠,
关键词：支持向量机(SVM), 线性插值法, 油温, 加权, 钟形函数,
发表日期：2020-12-10
- 文件大小:
- 838.34 KB
- 下载次数:
- 60
-
高速下载
|
|
